SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem

Autores
Minetti, Gabriela F.; Leguizamón, Guillermo; Alba, Enrique
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the past, the Fragment Assembly Problem has been solved efficiently by many metaheuristics. In this work, we propose a new one, called SAX, which consists in combining two metaheuristics: a trajectory method as Simulated Annealing and a population-based method as Genetic Algorithm. We also analyze the relative advantages of this hybridization against other assemblers from literature. From this analysis, we conclude that SAX improves the quality results found by other metaheuristic and non-metaheuristic assemblers for solving 100% of the largest instances for this problem.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
DNA Fragment Assembly Problem
Assembler
SAX
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/123746

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spelling SAX: a new and efficient assembler for solving DNA Fragment Assembly ProblemMinetti, Gabriela F.Leguizamón, GuillermoAlba, EnriqueCiencias InformáticasDNA Fragment Assembly ProblemAssemblerSAXIn the past, the Fragment Assembly Problem has been solved efficiently by many metaheuristics. In this work, we propose a new one, called SAX, which consists in combining two metaheuristics: a trajectory method as Simulated Annealing and a population-based method as Genetic Algorithm. We also analyze the relative advantages of this hybridization against other assemblers from literature. From this analysis, we conclude that SAX improves the quality results found by other metaheuristic and non-metaheuristic assemblers for solving 100% of the largest instances for this problem.Sociedad Argentina de Informática e Investigación Operativa2012-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf177-188http://sedici.unlp.edu.ar/handle/10915/123746enginfo:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/16_ASAI_2012.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2784info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:29:39Zoai:sedici.unlp.edu.ar:10915/123746Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:29:39.605SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
title SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
spellingShingle SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
Minetti, Gabriela F.
Ciencias Informáticas
DNA Fragment Assembly Problem
Assembler
SAX
title_short SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
title_full SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
title_fullStr SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
title_full_unstemmed SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
title_sort SAX: a new and efficient assembler for solving DNA Fragment Assembly Problem
dc.creator.none.fl_str_mv Minetti, Gabriela F.
Leguizamón, Guillermo
Alba, Enrique
author Minetti, Gabriela F.
author_facet Minetti, Gabriela F.
Leguizamón, Guillermo
Alba, Enrique
author_role author
author2 Leguizamón, Guillermo
Alba, Enrique
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
DNA Fragment Assembly Problem
Assembler
SAX
topic Ciencias Informáticas
DNA Fragment Assembly Problem
Assembler
SAX
dc.description.none.fl_txt_mv In the past, the Fragment Assembly Problem has been solved efficiently by many metaheuristics. In this work, we propose a new one, called SAX, which consists in combining two metaheuristics: a trajectory method as Simulated Annealing and a population-based method as Genetic Algorithm. We also analyze the relative advantages of this hybridization against other assemblers from literature. From this analysis, we conclude that SAX improves the quality results found by other metaheuristic and non-metaheuristic assemblers for solving 100% of the largest instances for this problem.
Sociedad Argentina de Informática e Investigación Operativa
description In the past, the Fragment Assembly Problem has been solved efficiently by many metaheuristics. In this work, we propose a new one, called SAX, which consists in combining two metaheuristics: a trajectory method as Simulated Annealing and a population-based method as Genetic Algorithm. We also analyze the relative advantages of this hybridization against other assemblers from literature. From this analysis, we conclude that SAX improves the quality results found by other metaheuristic and non-metaheuristic assemblers for solving 100% of the largest instances for this problem.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
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info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1850-2784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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177-188
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